H41D-1057
AGU Fall meeting 2011, San Francisco
Using transient ERT mapping to monitor infiltration pathways in a semi-arid cloud forest in Oman Jan Friesen1, Ulrike Werban2, Marco Pohle2, Abdullah Bawain3, Anke Hildebrandt1,4, Sabine Attinger1 1 Computational Hydrosystems, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany; 2 Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany; 3 Ministry of Regional Municipalities and Water Resources, Salalah, Sultanate of Oman; 4 Institute of Geosciences, Faculty of Chemical and Earth Science, Friedrich-Schiller-Univeryity Jena, Jena, Germany
Dhofar cloud forest system
Precipitation partitioning
Iraq Iran
B_int,1
UTM 40 N WGS 1984
Kuwait
A_int,1 A_int,2
Bahrain Qatar Saudi Arabia
United Arab Emirates
Egypt
Tower (fog gauge) Oman
sec t
Fence
B_edge
Rain/ Fog gauges
A_edge
Stemflow gauges Pithicellobium plots Leucaenia plots 236510
236520
236530
236540
236550
236560
236570
b)
An ERT transect was of a total length of 75 m was set up within a forest enclosure covering both forested and grassland area.
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tran
open field rain gauge
Legend
1893610
Djibouti
Stemflow/ Throughfall/ Net_precipitation/ Net_precipitation Net_precipitation Rainfall 22.6 (± 2.5) 77.4 (± 2.5) 88.8 (± 9.3) 42.7 (± 2.9) 57.3 (± 2.9) 123.7 (± 11.7) 0.0 (± 0.0) 0.0 (± 0.0) 100.0 (± 0.0)
ERT transect details
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Eritrea Ethiopia
ERT
Yemen
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A_int,3
Sudan
Forest 1 Forest 2 Grassland
b)
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Jordan
1893650
Syria Israel
a)
Table 1 Dhofar cloud forest precipitation budget (2008-2010)
Figure 3 Typical soil/ rock profile for the Dhofar mountains. Shallow soil layer (50 – 100 cm) above rock fractured with root/ soil channels.
Table 2 ERT transects
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a)
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In forests rainfall partitioning provides highly organized rainfall patterns caused by rainfall funneling through vegetation structure. The patterns of rainfall partitioning have been studied in great detail at a cloud forest enclosure in Dhofar, Oman. How the highly organized rainfall patterns on the surface are advancing into the root zone and deeper is the focus of this work.
ERT time lapse results
The three month long monsoon with its mainly fog and drizzle precipitation has distinct differences for rainfall partitioning over forest and grass land cover.
Figure 1 Tawi Attair cloud forest observatory (a) and schematic profile of the Dhofar mountains (b) during the monsoon season
Trees in the Dhofar Mountains function as excellent natural fog catchers that funnel extracted fog water through stemflow directly into the ground. Stemflow may provide a direct pathway from the stem along the roots to deeper soil water reservoirs.
100
a)
90 80
TF
TF
TF
TF
TF
a)
Electrodes Length Spacing [#] [m] [m] 108 75 1 64 32 0.5
b)
c) Figure 6 Short ERT transect with tree and rock outcrop position (a), leaf counts and tree canopies above each electrode (b), and forest, grassland, treeE08, as well as treeE12 regions(c).
SF
b)
Figure 4 Schematic ERT transect during installation (a, May 2011, dry season) and during August (b, peak of monsoon season).
70 Flux [mm d-1]
Long Short
Figure 8 Average resistivities for different landcover and time steps (I-V). On top the rainfall is plotted (rain data after 14 Aug is not yet available).
Figure 9 Resistivity profiles for different land cover. Line thickness depicts different timesteps; thin: timestep I, medium: timestep III, thick: timestep V.
60 50 40 30 20 10 0 9.5
11.0
12.5 12.6 Event TF [mm]
16.2
9.5
a)
Conclusions
Figure 2 Intensive throughfall experiment (a). Results from both throughfall(TF) and stemflow(SF) observations (b) show distinct differences in ground flux of both processes.
Electric resistivity tomography (ERT) has been used to visualize root water uptake from a tree orchard. In our approach we will use the advantage of ERT to look deep into the subsurface (10-20m) and combine it with subsequent ERT measurements in order to obtain a time series of ERT data. Transient ERT data aim at providing information about recharge patterns during the
b) Figure 7 Short ERT transect models for different timesteps. For models II to V model I was taken for the initial conditions (black triangles depict measured soil depths).
three month monsoon (mid-June to mid-September). To determine the effect of vegetation we conducted field observation for two land cover types, forest and grassland.
• Clear differences in total resistivity can be detected between forest and grass land cover • The ERT models all depict the soil/ bedrock boundary well • Resistivity differences between the two land cover types are reflected in the depth profiles
Contact: Jan Friesen Computational Hydrosystems, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany E-mail:
[email protected] / Phone: +49 (0)341 2351082
Figure 5 Schematic mapping of the electrodes as well as vegetation cover (a) and full transect model (b) based on the September 12th data (black triangles depict measured soil depths).
وزارة البلديات األقليمية وموارد املياه Ministry of Regional Municipalities & Water Resources
